IT AI Index

Index › Vendors › LangSmith · September 2026 Edition

2 categories · Named, not ranked

LangSmith

21Judge labels

0First choices

3Negative labels

10 of 12Models named it

2Categories

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

8 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. LangSmith was named 8 times in LLM gateways and 1 other category, where LiteLLM led with 38%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business12 of 44

under the label threshold

Mid-market32 of 63

under the label threshold

Enterprise15 of 62

under the label threshold

In llm gateways · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named LangSmith for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
LLM gateways and observability	Data platform	0%	32 of 63	29%	7	under 10 labels · led by LiteLLM at 38%
ML platforms	Data platform	0%	43 of 99	0%	1	under 10 labels · led by Azure Machine Learning at 17%

Movement

This is the first edition on this tier, so no move can be computed for LangSmith yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated LangSmith across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	1	0	1
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	1	0	0	1
Perplexity Sonar	0	0	0	0
Grok 4.1 Fast	1	0	0	1
Mistral Small	0	0	0	0
DeepSeek V4 Flash	0	1	0	1
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	0	0	1	1
Kimi K2	0	2	0	2
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	0	1	1

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct0 labelsNone

Paraphrase17 labelsNone

Comparative0 labelsNone

Budget-constrained0 labelsNone

Scale-constrained4 labelsNone

Negative0 labelsNone

First choiceAlternativeMentionNegative21 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Look at Weights & Biases (tracking/registry) + Braintrust/LangSmith (LLMOps/Evals)” Gemini 3.5 Flash · ML platforms · scale prompt · alternative

“LangSmith (If using LangChain/LangGraph)” Grok 4.1 Fast · LLM gateways · paraphrase prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Caveat: Can become expensive at high trace volumes, and it has a stronger lock-in effect if you move away from LangChain later.” Qwen 3.7 Flash · LLM gateways · paraphrase prompt · soft negative

“Tradeoff: Less flexible if you use other frameworks” MiniMax M2.5 · LLM gateways · paraphrase prompt · soft negative

Named alongside

The products named in the same answers as LangSmith, over the 21 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and LangSmith was named but was not.

ProductSame answerTook the first choice insteadHead to head

Langfuse16 of 216Not in the top three

Portkey12 of 216Not in the top three

Braintrust10 of 212Not in the top three

Helicone10 of 211Not in the top three

LiteLLM6 of 211Not in the top three

Datadog6 of 210Not in the top three

FastRouter4 of 211Not in the top three

Arize AI4 of 210Not in the top three

Confident AI3 of 212Not in the top three

Arize3 of 210Not in the top three

A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named LangSmith. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 16 of the 21 answers that named LangSmith and are not a share of its labels.

Domains cited

braintrust.dev12

confident-ai.com12

toolradar.com8

fast.io7

fastrouter.ai7

truefoundry.com7

firecrawl.dev6

helicone.ai6

langchain.com6

galileo.ai5

Seventy-six of the seventy-six domain citations in answers naming LangSmith came from somebody else's page.

Pages cited

toolradar.com/guides/best-llm-observability-tools8

braintrust.dev/articles/best-llm-gateways-observability-20267

braintrust.dev/articles/best-llm-routers-20266

confident-ai.com/knowledge-base/compare/best-enterprise-llm-observability-tools6

fast.io/resources/top-llm-observability-platforms6

firecrawl.dev/blog/best-llm-observability-tools6

langchain.com/resources/llm-observability-tools6

confident-ai.com/knowledge-base/compare/10-llm-observability-tools-to-evaluate-and-monitor5

Pages are listed as the models cited them.

Names read as LangSmith

What the judge wrote, as written, with how often. The vendor table decides that these count as LangSmith; a claim can dispute any of them.

LangSmith (by LangChain) 1Langsmith 1

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when LangSmith's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as LangSmith, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at langsmith.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.